Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Po-Hsuan Yen"'
Autor:
Po-Hsuan Yen, Justus Kavita Mutuku, Chung-Shin Yuan, Wei-Hsiang Chen, Chih-Cheng Wu, Chien-Sen Li
Publikováno v:
Process Safety and Environmental Protection. 172:579-587
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7d8814da1acd94add76b72911849b14f
https://doi.org/10.1016/j.psep.2023.02.015
https://doi.org/10.1016/j.psep.2023.02.015
Autor:
Po-Hsuan Yen, Chung-Shin Yuan, Chia-Wei Lee, Jun-Hao Ceng, Zi-You Huang, Kuan-Chen Chiang, I-Chieh Du, Yu-Lun Tseng, Ker-Yea Soong, Ming-Shiou Jeng
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a470d0539d389e5b93e257f6e85c16d0
https://doi.org/10.2139/ssrn.4371950
https://doi.org/10.2139/ssrn.4371950
Publikováno v:
Process Safety and Environmental Protection. 154:348-359
This research applied two suppression technologies of atomizing dust suppression (ADS) and spraying dust suppression (SDS) to eliminate fugitive dust emitted from coal stockpiles and further investigated their optimal operating parameters. In field t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7d11928987af44e06c1d19cab55fd8aa
https://doi.org/10.1016/j.psep.2021.08.026
https://doi.org/10.1016/j.psep.2021.08.026
Autor:
Po-Hsuan Yen, Chung-Shin Yuan, Jun-Hao Ceng, Kuan-Chen Chiang, Yu-Lun Tseng, Ker-Yea Soong, Ming-Shiou Jeng
Publikováno v:
The Science of the total environment. 851(Pt 2)
In this study, the concentrations of marine fine particles (PM
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0c3400965b53f8e73bed20a0817b78f5
https://pubmed.ncbi.nlm.nih.gov/36037889
https://pubmed.ncbi.nlm.nih.gov/36037889
Autor:
Chung-Shin, Yuan, Kuan-Chen, Chiang, Po-Hsuan, Yen, Jun-Hao, Ceng, Cheng-En, Lee, I-Chieh, Du, Ker-Yea, Soong, Ming-Shiou, Jeng
Publikováno v:
Environmental Pollution. 318:120899
This study explored the temporospatial distribution, gas-particle partition, and pollution sources of atmospheric speciated mercury (ASM) from the eastern offshore waters of the Taiwan Island (TI) to the northern South China Sea (SCS). Both gaseous a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a2a5f19c79d489e7e9e156eb15bed3dc
https://doi.org/10.1016/j.envpol.2022.120899
https://doi.org/10.1016/j.envpol.2022.120899
Autor:
Chung-Shin Yuan, Jun-Hao Ceng, Po-Hsuan Yen, Kuan-Chen Chiang, Yu-Lun Tseng, Kwok-Wai Wong, Ming-Shiou Jeng
Publikováno v:
Aerosol and Air Quality Research. 23:220350
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::00509085ffd62ace098d4967ad6db7de
https://doi.org/10.4209/aaqr.220350
https://doi.org/10.4209/aaqr.220350
Publikováno v:
ICCE-TW
In this paper, a deep metric learning method with combined loss of the triplet network and autoencoder is presented. Autoencoder is regarded as the regulation network to enable the embedding vector to have some latent features of the input image, and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::20632a87b3e885994e028f02fd17d840
https://doi.org/10.1109/icce-tw52618.2021.9603004
https://doi.org/10.1109/icce-tw52618.2021.9603004
Autor:
Po-Hsuan, Yen, Chung-Shin, Yuan, Chien-Hsing, Wu, Ming-Jie, Yeh, Yu-Lun, Tseng, Ker-Yea, Soong
Publikováno v:
The Science of the total environment. 806(Pt 2)
The fingerprints and source origins of marine PM
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::8eebc95a52a7bd4b8dd0e8ab7936f5a0
https://pubmed.ncbi.nlm.nih.gov/34597580
https://pubmed.ncbi.nlm.nih.gov/34597580
Autor:
Yu-Lun, Tseng, Chien-Hsing, Wu, Chung-Shin, Yuan, Gerry, Bagtasa, Po-Hsuan, Yen, Po-Hung, Cheng
Publikováno v:
The Science of the total environment. 793
This study inter-compared the concentration and chemical characteristics of PM
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::771d999a43466fb1eba876e160e561f2
https://pubmed.ncbi.nlm.nih.gov/34328987
https://pubmed.ncbi.nlm.nih.gov/34328987
Publikováno v:
ICCE-TW
In this paper, traditional one-hot encoded network is compared with three deep metric learning methods by using contrastive loss, triplet loss, and quadruplet loss on character classification task. Experimental results show that deep metric learning
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b5e83720ca93529849b00cab9a02c210
https://doi.org/10.1109/icce-taiwan49838.2020.9258229
https://doi.org/10.1109/icce-taiwan49838.2020.9258229